CN111738596A - Work order distribution method and device - Google Patents
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Abstract
The invention provides a work order dispatching method and a work order dispatching device, wherein the method comprises the following steps: responding to the work order dispatching request, obtaining the work orders to be dispatched contained in the work order dispatching request, calculating the similarity between the work orders to be dispatched and each historical work order contained in the vector space model according to the pre-constructed vector space model and the preset word position weight, taking the historical work order with the highest similarity as the target historical work order, and dispatching the work orders to be dispatched to the dispatching object corresponding to the target historical work order if the similarity between the work orders to be dispatched and the target historical work order is larger than the preset similarity threshold. Therefore, according to the technical scheme provided by the invention, the work order dispatching request is responded, the target historical work order is automatically determined, and when the similarity between the dispatching work order and the target historical work order is greater than the similarity threshold value, the work order to be dispatched is dispatched to the dispatching object corresponding to the target historical work order, so that the work order dispatching efficiency is improved, and the task processing efficiency is improved.
Description
Technical Field
The invention relates to the technical field of information processing, in particular to a work order dispatching method and device.
Background
In enterprise management, tasks are often distributed by way of work order dispatch, and work orders are dispatched to relevant employees, and the employees perform the tasks in the work orders.
Currently, the work order distribution is generally performed by the related enterprise staff. Under special circumstances, for example, a certain batch of sold products of enterprise have a problem, the condition that work order volume increases can appear, when work order volume is too big, often need consume a large amount of time cost and carry out work order distribution, lead to work order distribution untimely, and task processing efficiency is lower.
Disclosure of Invention
The application provides a work order dispatching method and a work order dispatching device, and aims to solve the problems that work orders are not dispatched in time and task processing efficiency is low due to the fact that a large amount of time cost needs to be consumed to dispatch the work orders.
In order to achieve the above object, the present application provides the following technical solutions:
a work order distribution method, comprising:
responding to a work order dispatching request, and acquiring a work order to be dispatched, wherein the work order is contained in the work order dispatching request;
calculating the similarity between the work order to be dispatched and each historical work order contained in the vector space model according to a pre-constructed vector space model and a preset word position weight;
taking the historical work order with the highest similarity as a target historical work order;
and if the similarity between the work order to be dispatched and the target historical work order is greater than a preset similarity threshold value, dispatching the work order to be dispatched to a dispatching object corresponding to the target historical work order.
The above method, optionally, the process of constructing the vector space model includes:
collecting a work order data set; the work order data set comprises a plurality of historical work orders and a distribution object corresponding to each historical work order; each historical work order comprises a title part and a text part;
performing word segmentation on each historical work order to obtain a plurality of title words and text words corresponding to each historical work order;
respectively carrying out word frequency statistics on each title vocabulary and each text vocabulary to obtain the word frequency corresponding to each title vocabulary and the word frequency corresponding to each text vocabulary;
aiming at each title vocabulary, mapping the title vocabulary into a title word vector according to the word frequency of the title vocabulary;
for each text vocabulary, mapping the text vocabulary into a text word vector according to the word frequency of the text vocabulary;
and constructing a vector space model according to the vector corresponding to each title word contained in each historical work order, the word vector corresponding to each text word contained in each historical work order and the dispatch object corresponding to the historical work order.
Optionally, in the method, the word position weight includes a word position weight of a title vocabulary and a word position weight of a text vocabulary, and the calculating the similarity between the work order to be dispatched and each historical work order included in the vector space model according to a pre-constructed vector space model and a preset word position weight includes:
calculating the title similarity of the work order to be dispatched and each historical work order according to the word vectors of the title words contained in each historical work order stored in the vector space model and the preset word position weight of each title word;
calculating the text similarity of the work order to be dispatched and each historical work order according to the word vectors of each text vocabulary contained in each historical work order stored in the vector space model and the preset word position weight of each text vocabulary;
and calculating the similarity between the work order to be dispatched and each historical work order according to the similarity between the title of the work order to be dispatched and each historical work order and the similarity between the text of the work order to be dispatched and each historical work order.
Optionally, in the foregoing method, the dispatching the to-be-dispatched work order to the dispatch object corresponding to the target historical work order includes:
judging whether a plurality of dispatching objects corresponding to the target historical work orders exist;
if the number of the dispatching objects corresponding to the target historical work order is multiple, selecting one dispatching object from the multiple dispatching objects to be determined as a target object based on each keyword of each dispatching object, and dispatching the work order to be dispatched to the target object; the keywords of each dispatching object are vocabularies, the word frequency of which is greater than a preset numerical value, in each vocabulary contained in the historical work order corresponding to the dispatching object, and the vocabularies comprise title vocabularies and text vocabularies;
and if the number of the dispatching objects corresponding to the target historical work order is not multiple, dispatching the work order to be dispatched to the dispatching object corresponding to the target historical work order.
Optionally, in the method, the selecting one served object from the multiple served objects to determine as the target object based on the keyword of each served object includes:
calculating the matching degree of each keyword of each dispatch object and each vocabulary contained in the work order to be dispatched;
and determining the served object corresponding to the highest matching degree as the target object.
A work order distribution apparatus comprising:
the acquiring unit is used for responding to the work order dispatching request and acquiring the work order to be dispatched, wherein the work order dispatching request comprises the work order to be dispatched;
the calculation unit is used for calculating the similarity between the work order to be dispatched and each historical work order contained in the vector space model according to a pre-constructed vector space model and a preset word position weight;
the determining unit is used for taking the historical work order with the highest similarity as a target historical work order;
and the dispatching unit is used for dispatching the work order to be dispatched to the dispatching object corresponding to the target historical work order if the similarity between the work order to be dispatched and the target historical work order is greater than a preset similarity threshold value.
The above apparatus, optionally, further comprises:
a collection unit for collecting a work order data set; the work order data set comprises a plurality of historical work orders and a distribution object corresponding to each historical work order; each historical work order comprises a title part and a text part;
the word segmentation unit is used for performing word segmentation on each historical work order to obtain a plurality of title words and text words corresponding to each historical work order;
the statistical unit is used for respectively carrying out word frequency statistics on each title vocabulary and each text vocabulary to obtain the word frequency corresponding to each title vocabulary and the word frequency corresponding to each text vocabulary;
the first mapping unit is used for mapping the title vocabulary into a title word vector according to the word frequency of the title vocabulary;
the second mapping unit is used for mapping each text vocabulary into a text word vector according to the word frequency of the text vocabulary;
and the construction unit is used for constructing a vector space model according to the vector corresponding to each title word contained in each historical work order, the word vector corresponding to each text word contained in each historical work order and the dispatch object corresponding to the historical work order.
Optionally, in the apparatus described above, the word position weight includes a word position weight of a title vocabulary and a word position weight of a text vocabulary, and the calculating unit calculates a similarity between the work order to be distributed and each historical work order included in the vector space model according to a pre-constructed vector space model and a preset word position weight, and is configured to:
calculating the title similarity of the work order to be dispatched and each historical work order according to the word vectors of the title words contained in each historical work order stored in the vector space model and the preset word position weight of each title word;
calculating the text similarity of the work order to be dispatched and each historical work order according to the word vectors of each text vocabulary contained in each historical work order stored in the vector space model and the preset word position weight of each text vocabulary;
and calculating the similarity between the work order to be dispatched and each historical work order according to the similarity between the title of the work order to be dispatched and each historical work order and the similarity between the text of the work order to be dispatched and each historical work order.
The above apparatus, optionally, the dispatch unit includes:
the judging subunit is used for judging whether a plurality of distribution objects corresponding to the target historical work order exist;
the first dispatching subunit is used for selecting one dispatching object from the dispatching objects to determine the dispatching object as a target object based on each keyword of each dispatching object if the dispatching objects corresponding to the target historical work order are multiple, and dispatching the work order to be dispatched to the target object; the keywords of each dispatching object are vocabularies, the word frequency of which is greater than a preset numerical value, in each vocabulary contained in the historical work order corresponding to the dispatching object, and the vocabularies comprise title vocabularies and text vocabularies;
and the second dispatching subunit is used for dispatching the work orders to be dispatched to the dispatching objects corresponding to the target historical work orders if the dispatching objects corresponding to the target historical work orders are not multiple.
In the foregoing apparatus, optionally, the first serving sub-unit performs, based on the keyword of each served object, to select one served object from the multiple served objects and determine the one served object as the target object, and is configured to:
calculating the matching degree of each keyword of each dispatch object and each vocabulary contained in the work order to be dispatched;
and determining the served object corresponding to the highest matching degree as the target object.
A storage medium comprising stored instructions, wherein the instructions, when executed, control a device on which the storage medium is located to perform the above-described work order dispatching method.
An electronic device comprising a memory, and one or more instructions stored in the memory and configured to be executed by one or more processors to perform the above work order dispatch method.
Compared with the prior art, the invention has the following advantages:
the invention provides a work order dispatching method and a work order dispatching device, wherein the method comprises the following steps: responding to the work order dispatching request, obtaining the work orders to be dispatched contained in the work order dispatching request, calculating the similarity between the work orders to be dispatched and each historical work order contained in the vector space model according to the pre-constructed vector space model and the preset word position weight, taking the historical work order with the highest similarity as the target historical work order, and dispatching the work orders to be dispatched to the dispatching object corresponding to the target historical work order if the similarity between the work orders to be dispatched and the target historical work order is larger than the preset similarity threshold. Therefore, according to the technical scheme provided by the invention, the work order dispatching request is responded, the target historical work order is automatically determined, and when the similarity between the dispatching work order and the target historical work order is greater than the similarity threshold value, the work order to be dispatched is dispatched to the dispatching object corresponding to the target historical work order, so that the work order dispatching efficiency is improved, and the task processing efficiency is improved.
Drawings
In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the embodiments or the prior art will be briefly described below, it is obvious that the drawings in the following description are only embodiments of the present invention, and for those skilled in the art, other drawings can be obtained according to the provided drawings without creative efforts.
FIG. 1 is a flow chart of a method for dispatching a work order according to the present invention;
FIG. 2 is a flowchart of another method of the present invention for work order dispatch;
FIG. 3 is a flow chart of another method of the present invention for work order dispatch;
FIG. 4 is a schematic structural diagram of a work order dispatching device provided in the present invention;
fig. 5 is a schematic structural diagram of an electronic device provided in the present invention.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
The embodiment of the invention provides a work order dispatching method, which can be applied to various system platforms, wherein an execution main body of the work order dispatching method can be a processor running on a computer, and a flow chart of the work order dispatching method is shown in figure 1 and specifically comprises the following steps:
s101, responding to the work order dispatching request, and obtaining the work order to be dispatched, wherein the work order is contained in the work order dispatching request.
Responding to the work order dispatching request, and obtaining the work orders to be dispatched, wherein the work order dispatching request is contained in the work order dispatching request, the user can send the work order dispatching request through a plurality of channels, optionally, the channels include but are not limited to a webpage, an APP and an API, and when the work order dispatching request sent by the user is received, the work order dispatching request is responded, and the work orders to be dispatched, contained in the work order dispatching request, are obtained.
S102, calculating the similarity between the work order to be dispatched and each historical work order contained in the vector space model according to the pre-constructed vector space model and the preset word position weight.
The vector space model is pre-constructed, wherein the construction process of the vector space model participates in fig. 2, and specifically comprises the following steps:
s201, collecting a work order data set.
And collecting a work order data set, wherein the work order data set comprises a plurality of historical work orders and a distribution object corresponding to each historical work order, and each historical work order comprises a title part and a text part.
Alternatively, the historical work order may be a work order over the course of a year.
Alternatively, the work order data set may be collected by a full-text search engine.
S202, performing word segmentation on each historical work order to obtain a plurality of title words and text words corresponding to each historical work order.
And respectively segmenting the title part and the text part contained in each historical work order to obtain a plurality of title words corresponding to each historical work order and a plurality of text words corresponding to each historical work order.
Optionally, the word segmentation result may be subjected to data preprocessing to remove stop words, language-atmosphere words, nonsense words, and the like in the title words and the text words, so as to improve data quality.
It should be noted that the word segmentation method adopted for segmenting words of each historical work order is the prior art, and please refer to the prior word segmentation method, which is not described herein again.
S203, respectively carrying out word frequency statistics on each title vocabulary and each text vocabulary to obtain the word frequency corresponding to each title vocabulary and the word frequency corresponding to each text vocabulary.
And optionally, counting the frequency of each text vocabulary appearing in the text vocabulary corresponding to each historical work order by adopting reverse document frequency, and counting the frequency of each title vocabulary appearing in the title vocabulary corresponding to each historical work order.
Optionally, the method may further include counting, for each historical work order corresponding to each dispatch object, a keyword corresponding to each dispatch object, that is, for the word frequency of each title word included in each historical work order corresponding to the dispatch object, if the word frequency of the title word is greater than a preset value, taking the title word as the keyword corresponding to the dispatch object, and for the word frequency of each text word included in each historical work order corresponding to the dispatch object, if the word frequency of the text word is greater than a preset value, taking the text word as the keyword specified by the dispatch object.
It should be noted that the keyword corresponding to each served object is used to indicate that the served object often processes the work order related to the keyword.
And S204, aiming at each title vocabulary, mapping the title vocabulary into a title word vector according to the word frequency of the title vocabulary.
S205, aiming at each text vocabulary, mapping the text vocabulary into text word vectors according to the word frequency of the text vocabulary.
S206, constructing a vector space model according to the vector corresponding to each title word contained in each historical work order, the word vector corresponding to each text word contained in each historical work order and the dispatch object corresponding to the historical work order.
And constructing a vector space model according to the vector corresponding to each title word and the vector corresponding to each text word contained in each historical work order and the dispatching object corresponding to the historical work order. In the vector space model, each title vocabulary and each text word are represented in the form of a vector.
In the method provided by the embodiment of the invention, word segmentation processing is carried out on the work orders to be dispatched, and the similarity between the work orders to be dispatched and each historical work order contained in the vector space model is calculated according to the vector space model, the preset word position weight and the cosine similarity.
S103: and taking the historical work order with the highest similarity as a target historical work order.
According to the similarity of the work orders to be dispatched and each historical work order contained in the vector space model, sequencing the historical work orders according to the sequence of the similarity from high to low or from low to high, and selecting the first or the last historical work order from the sequenced historical work orders as a target historical work order, wherein if the sequence of the similarity from high to bottom is adopted, the first historical work order is selected as the target historical work order; and if the work orders are sorted according to the sequence from low similarity to high similarity, selecting the last historical work order as the target historical work order. It should be noted that the target historical work order is the historical work order with the highest similarity to the work order to be dispatched in each historical work order.
And S104, if the similarity between the work order to be dispatched and the target historical work order is greater than a preset similarity threshold value, dispatching the work order to be dispatched to a dispatching object corresponding to the target historical work order.
And judging whether the similarity between the work order to be dispatched and the target historical work order is greater than a preset similarity threshold, if so, dispatching the work order to be dispatched to a dispatching object corresponding to the target historical work order, and if not, triggering manual dispatching of the work order to be dispatched.
The process of dispatching the work order to be dispatched to the dispatching object corresponding to the target historical work order comprises the following steps:
judging whether a plurality of dispatching objects corresponding to the target historical work orders exist;
if the number of the dispatching objects corresponding to the target historical work order is multiple, selecting one dispatching object from the multiple dispatching objects based on each keyword of each dispatching object to determine as a target object, and dispatching the work order to be dispatched to the target object;
and if the number of the dispatching objects corresponding to the target historical work order is not multiple, dispatching the work order to be dispatched to the dispatching object corresponding to the target historical work order.
In the method provided by the embodiment of the present invention, a plurality of historical work orders may be the same work order, so that the similarity between the work order to be dispatched and the plurality of historical work orders may be the same, if the similarity between the work order to be dispatched and the plurality of historical work orders is the same and the similarity is the highest, the determined target historical work orders are multiple, and if the determined target historical work orders are multiple, the dispatch objects corresponding to the target historical work orders are also multiple.
Judging whether the dispatching objects corresponding to the target historical work orders are multiple, if so, determining one dispatching object from the multiple dispatching objects as the target object, optionally, determining the target object from the multiple dispatching objects according to the keywords corresponding to each dispatching object, wherein the keywords corresponding to each dispatching object are the words with the word frequency larger than a preset value in the words contained in the historical work orders corresponding to the dispatching objects, and the words comprise the title words and the text words, namely, the keywords corresponding to each dispatching object are the title words and the text words contained in the historical work orders corresponding to the dispatching objects, and the word frequency is larger than the preset value; and if the number of the dispatching objects corresponding to the target historical work order is not multiple, namely one, directly dispatching the work order to be dispatched to the dispatching object corresponding to the target historical work order.
The specific process of determining the target object from the plurality of the dispatched objects according to the keyword corresponding to each dispatched object comprises the following steps:
calculating the matching degree of each keyword of each dispatch object and each vocabulary contained in the work order to be dispatched;
and determining the served object corresponding to the highest matching degree as the target object.
In the method provided by the implementation of the invention, each keyword of each dispatch object is respectively matched with each vocabulary contained in the work order to be dispatched, the matching degree is calculated, and the dispatch object corresponding to the highest matching degree is determined as the target object. The matching degree is used for indicating the matching degree of each keyword of the dispatching object and each vocabulary contained in the work order to be dispatched.
The above-mentioned specific process of determining a target object from a plurality of dispatch objects is illustrated as follows:
the keywords of the dispatching object A comprise a keyword a, a keyword B and a keyword c, the keywords of the dispatching object B comprise a keyword c, a keyword e and a keyword f, the vocabularies contained in the work order to be dispatched are a, B, e and h, the matching degree of the vocabularies contained in the work order to be dispatched and the keywords of the dispatching object A is 50%, the matching degree of the vocabularies contained in the work order to be dispatched and the keywords of the dispatching object A is 25%, and the dispatching object A is determined to be the target object.
The work order dispatching method provided by the embodiment of the invention responds to the work order dispatching request, obtains the work orders to be dispatched contained in the work order dispatching request, calculates the similarity between the work orders to be dispatched and each historical work order contained in the vector space model according to the pre-constructed vector space model and the preset word position weight, takes the historical work order with the highest similarity as the target historical work order, and dispatches the work orders to be dispatched to the dispatching object corresponding to the target historical work order if the similarity between the work orders to be dispatched and the target historical work order is greater than the preset similarity threshold value. By applying the work order dispatching method provided by the embodiment of the invention, the work order dispatching request is responded, the target historical work order is automatically determined, and when the similarity between the dispatching work order and the target historical work order is greater than the similarity threshold value, the work order to be dispatched is dispatched to the dispatching object corresponding to the target historical work order, so that the work order dispatching efficiency is improved, and the task processing efficiency is improved.
In the embodiment of the present invention, the word weight mentioned in fig. 1 includes a word position weight of a title vocabulary and a word position weight of a text vocabulary, and the similarity between the work order to be dispatched and each historical work order included in the vector space model is calculated according to the pre-constructed vector space model and the preset word position weight in step S102, where the flowchart is shown in fig. 3, and includes the following steps:
s301, calculating the title similarity of the work order to be dispatched and each historical work order according to the word vectors of the title words contained in each historical work order stored in the vector space model and the preset word position weight of each title word.
Before calculating the title similarity of the work order to be dispatched and each historical work order, the method further comprises the steps of carrying out word segmentation on the work order to be dispatched to obtain a plurality of words corresponding to the work order to be dispatched, mapping each word corresponding to the work order to be dispatched into a word vector, and calculating the title similarity of the work order to be dispatched and each historical work order based on the word vector of each word corresponding to the work order to be dispatched, the word vector of each title word contained in each historical work order stored in the vector space model and the preset word position weight of each title word.
The similarity between the work order to be dispatched and a single title word of the historical work order can be calculated through the following formula:
wherein m isiWord vectors representing the ith head word of the work order to be dispatched, njWord vector, cos (m), representing the jth heading vocabulary of the historical work orderi,nj) Represents miAnd njThe similarity of (c).
In the method provided by the embodiment of the present invention, the title similarity between the to-be-dispatched work order and the historical work order is related to the similarity and the word position weight of each title vocabulary, for example, the to-be-dispatched work order includes a title vocabulary a1, a title vocabulary B1, and a title vocabulary C1, the historical work order a includes a title vocabulary a2, a title vocabulary B2, and a title vocabulary C2, if the word position weight corresponding to a2 is w1, the word position weight corresponding to B2 is w2, the word position weight corresponding to C2 is w3, the similarity between a1 and a2 is cos1, the similarity between B1 and B2 is cos2, and the similarity between C1 and C1 is cos1, then the title similarity between the to-be-dispatched work order and the historical work order is cos 1+ cos 1.
S302, calculating the text similarity of the work order to be dispatched and each historical work order according to the word vectors of each text vocabulary contained in each historical work order stored in the vector space model and the preset word position weight of each text vocabulary.
In the method provided by the embodiment of the invention, the calculation process of the text similarity of the work order to be dispatched and each historical work order is similar to the calculation process of the title similarity of the work order to be dispatched and each historical work order, and the description is omitted here.
S303, calculating the similarity between the work order to be dispatched and each historical work order according to the title similarity between the work order to be dispatched and each historical work order and the text similarity between the work order to be dispatched and each historical work order.
And calculating the title similarity of the historical work order and superimposing the text similarity of the historical work order on each historical work order to obtain the similarity of the historical work order and the work order to be dispatched, optionally, directly superimposing the title similarity of the historical work order on the text similarity of the historical work order, or superimposing the title similarity of the historical work order on the text similarity of the historical work order according to a preset percentage, for example, presetting the title percentage as 40% and the text percentage as 60%, and after calculating to obtain the title similarity and the text similarity of the historical work order and the work order to be dispatched, adding the title similarity of 40% and the text similarity of 60% to obtain the similarity of the historical work order and the work order to be dispatched.
In the work order dispatching method provided by the embodiment of the invention, the header similarity and the text similarity of the work order to be dispatched and each historical work order are calculated according to the word vectors of each title vocabulary and each text vocabulary contained in each historical work order stored in the vector space model, the word position weight of the title vocabulary and the word position weight of the text vocabulary, and the header similarity of the historical work order is superposed on the text similarity of the historical work order aiming at each historical work order to obtain the similarity of the historical work order and the work order to be dispatched. The inventor researches and finds that the importance degrees of the title words at different positions in the work order are different and the importance degrees of the text words at different positions are also different, so that the similarity is calculated based on the word position weight, and the accuracy of determining the target historical work order can be improved.
Corresponding to the method described in fig. 1, an embodiment of the present invention further provides a work order dispatching device, which is used for specifically implementing the method in fig. 1, and a schematic structural diagram of the work order dispatching device is shown in fig. 4, and specifically includes:
an obtaining unit 401, configured to respond to a work order dispatching request, and obtain a work order to be dispatched, where the work order dispatching request includes the work order;
a calculating unit 402, configured to calculate, according to a pre-constructed vector space model and preset word position weights, a similarity between the work order to be dispatched and each historical work order included in the vector space model;
a determining unit 403, configured to use the historical work order with the highest similarity as a target historical work order;
and the dispatching unit 404 is configured to dispatch the work order to be dispatched to the dispatching object corresponding to the target historical work order if the similarity between the work order to be dispatched and the target historical work order is greater than a preset similarity threshold.
The work order dispatching device provided by the embodiment of the invention responds to the work order dispatching request, obtains the work orders to be dispatched contained in the work order dispatching request, calculates the similarity between the work orders to be dispatched and each historical work order contained in the vector space model according to the pre-constructed vector space model and the preset word position weight, takes the historical work order with the highest similarity as the target historical work order, and dispatches the work orders to be dispatched to the dispatching object corresponding to the target historical work order if the similarity between the work orders to be dispatched and the target historical work order is greater than the preset similarity threshold value. The work order dispatching device provided by the embodiment of the invention responds to the work order dispatching request, automatically determines the target historical work order, and dispatches the work order to be dispatched to the dispatching object corresponding to the target historical work order when the similarity between the dispatching work order and the target historical work order is greater than the similarity threshold value, so that the work order dispatching efficiency is improved, and the task processing efficiency is improved.
In an embodiment of the present invention, based on the foregoing solution, the method may further include:
a collection unit for collecting a work order data set; the work order data set comprises a plurality of historical work orders and a distribution object corresponding to each historical work order; each historical work order comprises a title part and a text part;
the word segmentation unit is used for performing word segmentation on each historical work order to obtain a plurality of title words and text words corresponding to each historical work order;
the statistical unit is used for respectively carrying out word frequency statistics on each title vocabulary and each text vocabulary to obtain the word frequency corresponding to each title vocabulary and the word frequency corresponding to each text vocabulary;
the first mapping unit is used for mapping the title vocabulary into a title word vector according to the word frequency of the title vocabulary;
the second mapping unit is used for mapping each text vocabulary into a text word vector according to the word frequency of the text vocabulary;
and the construction unit is used for constructing a vector space model according to the vector corresponding to each title word contained in each historical work order, the word vector corresponding to each text word contained in each historical work order and the dispatch object corresponding to the historical work order.
In an embodiment of the present invention, based on the foregoing solution, the word position weight includes a word position weight of a title vocabulary and a word position weight of a text vocabulary, the calculating unit 402 calculates a similarity between the work order to be dispatched and each historical work order included in the vector space model according to a pre-constructed vector space model and a preset word position weight, and is configured to:
calculating the title similarity of the work order to be dispatched and each historical work order according to the word vectors of the title words contained in each historical work order stored in the vector space model and the preset word position weight of each title word;
calculating the text similarity of the work order to be dispatched and each historical work order according to the word vectors of each text vocabulary contained in each historical work order stored in the vector space model and the preset word position weight of each text vocabulary;
and calculating the similarity between the work order to be dispatched and each historical work order according to the similarity between the title of the work order to be dispatched and each historical work order and the similarity between the text of the work order to be dispatched and each historical work order.
In an embodiment of the present invention, based on the foregoing solution, the dispatching unit 404 is configured to:
the judging subunit is used for judging whether a plurality of distribution objects corresponding to the target historical work order exist;
the first dispatching subunit is used for selecting one dispatching object from the dispatching objects to determine the dispatching object as a target object based on each keyword of each dispatching object if the dispatching objects corresponding to the target historical work order are multiple, and dispatching the work order to be dispatched to the target object; the keywords of each dispatching object are vocabularies, the word frequency of which is greater than a preset numerical value, in each vocabulary contained in the historical work order corresponding to the dispatching object, and the vocabularies comprise title vocabularies and text vocabularies;
and the second dispatching subunit is used for dispatching the work orders to be dispatched to the dispatching objects corresponding to the target historical work orders if the dispatching objects corresponding to the target historical work orders are not multiple.
In an embodiment of the present invention, based on the foregoing solution, the first serving sub-unit performs selecting one served object from the plurality of served objects to be determined as the target object based on the keyword of each served object, and is configured to:
calculating the matching degree of each keyword of each dispatch object and each vocabulary contained in the work order to be dispatched;
and determining the served object corresponding to the highest matching degree as the target object.
The embodiment of the invention also provides a storage medium, which comprises a stored instruction, wherein when the instruction runs, the equipment where the storage medium is located is controlled to execute the work order dispatching method.
An electronic device is provided in an embodiment of the present invention, and the structural diagram of the electronic device is shown in fig. 5, which specifically includes a memory 501 and one or more instructions 502, where the one or more instructions 502 are stored in the memory 501, and are configured to be executed by one or more processors 503 to perform the following operations according to the one or more instructions 502:
responding to a work order dispatching request, and acquiring a work order to be dispatched, wherein the work order is contained in the work order dispatching request;
calculating the similarity between the work order to be dispatched and each historical work order contained in the vector space model according to a pre-constructed vector space model and a preset word position weight;
taking the historical work order with the highest similarity as a target historical work order;
and if the similarity between the work order to be dispatched and the target historical work order is greater than a preset similarity threshold value, dispatching the work order to be dispatched to a dispatching object corresponding to the target historical work order.
It should be noted that, in the present specification, the embodiments are all described in a progressive manner, each embodiment focuses on differences from other embodiments, and the same and similar parts among the embodiments may be referred to each other. For the device-like embodiment, since it is basically similar to the method embodiment, the description is simple, and for the relevant points, reference may be made to the partial description of the method embodiment.
Finally, it should also be noted that, herein, relational terms such as first and second, and the like may be used solely to distinguish one entity or action from another entity or action without necessarily requiring or implying any actual such relationship or order between such entities or actions. Also, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus. Without further limitation, an element defined by the phrase "comprising an … …" does not exclude the presence of other identical elements in a process, method, article, or apparatus that comprises the element.
For convenience of description, the above devices are described as being divided into various units by function, and are described separately. Of course, the functions of the units may be implemented in the same software and/or hardware or in a plurality of software and/or hardware when implementing the invention.
From the above description of the embodiments, it is clear to those skilled in the art that the present invention can be implemented by software plus necessary general hardware platform. Based on such understanding, the technical solutions of the present invention may be embodied in the form of a software product, which may be stored in a storage medium, such as ROM/RAM, magnetic disk, optical disk, etc., and includes instructions for causing a computer device (which may be a personal computer, a server, or a network device, etc.) to execute the method according to the embodiments or some parts of the embodiments.
The method and the device for dispatching the work orders are described in detail, a specific example is applied in the method to explain the principle and the implementation mode of the invention, and the description of the embodiment is only used for helping to understand the method and the core idea of the invention; meanwhile, for a person skilled in the art, according to the idea of the present invention, there may be variations in the specific embodiments and the application scope, and in summary, the content of the present specification should not be construed as a limitation to the present invention.
Claims (10)
1. A work order dispatching method is characterized by comprising the following steps:
responding to a work order dispatching request, and acquiring a work order to be dispatched, wherein the work order is contained in the work order dispatching request;
calculating the similarity between the work order to be dispatched and each historical work order contained in the vector space model according to a pre-constructed vector space model and a preset word position weight;
taking the historical work order with the highest similarity as a target historical work order;
and if the similarity between the work order to be dispatched and the target historical work order is greater than a preset similarity threshold value, dispatching the work order to be dispatched to a dispatching object corresponding to the target historical work order.
2. The method of claim 1, wherein the vector space model is constructed by a process comprising:
collecting a work order data set; the work order data set comprises a plurality of historical work orders and a distribution object corresponding to each historical work order; each historical work order comprises a title part and a text part;
performing word segmentation on each historical work order to obtain a plurality of title words and text words corresponding to each historical work order;
respectively carrying out word frequency statistics on each title vocabulary and each text vocabulary to obtain the word frequency corresponding to each title vocabulary and the word frequency corresponding to each text vocabulary;
aiming at each title vocabulary, mapping the title vocabulary into a title word vector according to the word frequency of the title vocabulary;
for each text vocabulary, mapping the text vocabulary into a text word vector according to the word frequency of the text vocabulary;
and constructing a vector space model according to the vector corresponding to each title word contained in each historical work order, the word vector corresponding to each text word contained in each historical work order and the dispatch object corresponding to the historical work order.
3. The method of claim 2, wherein the word position weight includes a word position weight of a title vocabulary and a word position weight of a text vocabulary, and the calculating the similarity between the work order to be dispatched and each historical work order included in the vector space model according to a pre-constructed vector space model and a preset word position weight comprises:
calculating the title similarity of the work order to be dispatched and each historical work order according to the word vectors of the title words contained in each historical work order stored in the vector space model and the preset word position weight of each title word;
calculating the text similarity of the work order to be dispatched and each historical work order according to the word vectors of each text vocabulary contained in each historical work order stored in the vector space model and the preset word position weight of each text vocabulary;
and calculating the similarity between the work order to be dispatched and each historical work order according to the similarity between the title of the work order to be dispatched and each historical work order and the similarity between the text of the work order to be dispatched and each historical work order.
4. The method as claimed in claim 2, wherein said dispatching the to-be-dispatched work order to the dispatch object corresponding to the target historical work order comprises:
judging whether a plurality of dispatching objects corresponding to the target historical work orders exist;
if the number of the dispatching objects corresponding to the target historical work order is multiple, selecting one dispatching object from the multiple dispatching objects to be determined as a target object based on each keyword of each dispatching object, and dispatching the work order to be dispatched to the target object; the keywords of each dispatching object are vocabularies, the word frequency of which is greater than a preset numerical value, in each vocabulary contained in the historical work order corresponding to the dispatching object, and the vocabularies comprise title vocabularies and text vocabularies;
and if the number of the dispatching objects corresponding to the target historical work order is not multiple, dispatching the work order to be dispatched to the dispatching object corresponding to the target historical work order.
5. The method of claim 4, wherein selecting a served object from a plurality of served objects to be determined as a target object based on the keyword of each served object comprises:
calculating the matching degree of each keyword of each dispatch object and each vocabulary contained in the work order to be dispatched;
and determining the served object corresponding to the highest matching degree as the target object.
6. A work order distribution device, comprising:
the acquiring unit is used for responding to the work order dispatching request and acquiring the work order to be dispatched, wherein the work order dispatching request comprises the work order to be dispatched;
the calculation unit is used for calculating the similarity between the work order to be dispatched and each historical work order contained in the vector space model according to a pre-constructed vector space model and a preset word position weight;
the determining unit is used for taking the historical work order with the highest similarity as a target historical work order;
and the dispatching unit is used for dispatching the work order to be dispatched to the dispatching object corresponding to the target historical work order if the similarity between the work order to be dispatched and the target historical work order is greater than a preset similarity threshold value.
7. The apparatus of claim 6, further comprising:
a collection unit for collecting a work order data set; the work order data set comprises a plurality of historical work orders and a distribution object corresponding to each historical work order; each historical work order comprises a title part and a text part;
the word segmentation unit is used for performing word segmentation on each historical work order to obtain a plurality of title words and text words corresponding to each historical work order;
the statistical unit is used for respectively carrying out word frequency statistics on each title vocabulary and each text vocabulary to obtain the word frequency corresponding to each title vocabulary and the word frequency corresponding to each text vocabulary;
the first mapping unit is used for mapping the title vocabulary into a title word vector according to the word frequency of the title vocabulary;
the second mapping unit is used for mapping each text vocabulary into a text word vector according to the word frequency of the text vocabulary;
and the construction unit is used for constructing a vector space model according to the vector corresponding to each title word contained in each historical work order, the word vector corresponding to each text word contained in each historical work order and the dispatch object corresponding to the historical work order.
8. The apparatus according to claim 7, wherein the word position weight includes a word position weight of a title vocabulary and a word position weight of a body vocabulary, and the calculating unit performs calculating the similarity between the work order to be dispatched and each historical work order included in the vector space model according to a pre-constructed vector space model and a preset word position weight, and is configured to:
calculating the title similarity of the work order to be dispatched and each historical work order according to the word vectors of the title words contained in each historical work order stored in the vector space model and the preset word position weight of each title word;
calculating the text similarity of the work order to be dispatched and each historical work order according to the word vectors of each text vocabulary contained in each historical work order stored in the vector space model and the preset word position weight of each text vocabulary;
and calculating the similarity between the work order to be dispatched and each historical work order according to the similarity between the title of the work order to be dispatched and each historical work order and the similarity between the text of the work order to be dispatched and each historical work order.
9. The apparatus of claim 7, wherein the dispatch unit comprises:
the judging subunit is used for judging whether a plurality of distribution objects corresponding to the target historical work order exist;
the first dispatching subunit is used for selecting one dispatching object from the dispatching objects to determine the dispatching object as a target object based on each keyword of each dispatching object if the dispatching objects corresponding to the target historical work order are multiple, and dispatching the work order to be dispatched to the target object; the keywords of each dispatching object are vocabularies, the word frequency of which is greater than a preset numerical value, in each vocabulary contained in the historical work order corresponding to the dispatching object, and the vocabularies comprise title vocabularies and text vocabularies;
and the second dispatching subunit is used for dispatching the work orders to be dispatched to the dispatching objects corresponding to the target historical work orders if the dispatching objects corresponding to the target historical work orders are not multiple.
10. The apparatus of claim 9, wherein the first serving sub-unit performs the following steps of selecting one serving object from the plurality of serving objects as the target object based on the keyword of each serving object:
calculating the matching degree of each keyword of each dispatch object and each vocabulary contained in the work order to be dispatched;
and determining the served object corresponding to the highest matching degree as the target object.
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